pv_info
Connection details of a PV: serving IOC host:port, native type, element count, and whether this
This record as markdown: /tools/lab-instrument-mcps/pv-info.md
What pv_info does on Pypi:labmcp Alicat
AI agents call pv_info to retrieve information from Pypi:labmcp Alicat without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why pv_info is rated Low
Retrieves connection metadata about a process variable without modifying instrument state or triggering operations.
From the tool's definition Connection details, serving IOC host:port, native type, element count
Attacks that exploit this kind of access
The rule that runs pv_info safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Pypi:labmcp Alicat, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For pv_info, this is the rule to start with:
pv_info is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Pypi:labmcp Alicat, apply this rule, and every pv_info call is checked against it from then on.
Questions about pv_info
Connection details of a PV: serving IOC host:port, native type, element count, and whether this. It is categorised as a Read tool in the Pypi:labmcp Alicat MCP Server, which means it retrieves data without modifying state.
Register the Pypi:labmcp Alicat MCP server in PolicyLayer and add a rule for pv_info: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Pypi:labmcp Alicat. Nothing to install.
pv_info is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the pv_info rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for pv_info. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
pv_info is provided by the Pypi:labmcp Alicat MCP server (pypi:labmcp-alicat). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Pypi:labmcp Alicat, and thousands of servers like it.
This server
Across the catalogue